Predicting the habitat suitability of the invasive white mango scale,Aulacaspis tubercularis; Newstead, 1906 (Hemiptera: Diaspididae) using bioclimatic variables

Abstract

BACKGROUND: The white mango scale, Aulacaspis tubercularis (Hemiptera: Diaspididae), is an invasive pest that threatens the production of several crops of commercial value including mango. Though it is an important pest, little is known about its biology and ecology. Specifically, information on habitat suitability of A. tubercularis occurrence and potential distribution under climate change is largely unknown. In this study, we used four ecological niche models, namely maximum entropy, random forest, generalized additive models, and classification and regression trees to predict the habitat suitability of A. tubercularis under current and future [representative concentration pathways (RCPs): RCP4.5 and RCP8.5 of the year 2070] climatic scenarios, using bioclimatic variables. Models' performance was evaluated using the true skill statistic (TSS), the area under the curve (AUC), correlation (COR), and the deviance. RESULTS: All models sufficiently predicted the occurrence of A. tubercularis with high accuracy (AUC ≥ 0.93, TSS ≥ 0.81 and COR ≥ 0.77). The random forest algorithm had the highest accuracy among the four models (AUC = 0.99, TSS = 0.93, COR = 0.90, deviance = 0.26). Temperature seasonality (Bio4), mean temperature of the driest quarter (Bio9), and precipitation seasonality (Bio15) were the most important variables influencing A. tubercularis occurrence. Models' predictions showed that countries in east, south, and west Africa are highly suitable for A. tubercularis establishment under current conditions. Similarly,

Climate change may drive the distribution of tribe Zyginelline pests in China and the Indo‐China Peninsula to shift towards higher latitude river‐mountain systems

“…Spatial refinement of the species distribution points was achieved by randomly retaining one distribution point within the overlapping buffer zone 26 . Thus, the minimum ground distance between any two closely spaced distribution points was 5 km 9 . Based on the earlier operations, 117 distribution points were selected, one of which lacked environmental data, resulting in 116 qualified distribution points for modeling, comprising 54 species from 15 genera (Supporting Information Table S1).…”

“…We used the ‘sdmData’ function to generate 1000 ‘pseudo‐absence’ points randomly before combining them with 116 distribution records for modeling. Research has shown that randomly selecting pseudo‐absence data in species distribution modeling can yield the most reliable ENMs 40 and the selection of these 1000 ‘pseudo‐absence’ points was based on recommendations from previous studies 9,19,41,42 . Moreover, the 116 distribution records were sufficient for accurate modeling since accuracy was near maximum when there were 50 data points 19,43 .…”

“…[28][29][30] Bioclimatic variables governing the eco-physiological suitability of bioclimatic states have greater biological significance than simply temperature and precipitation levels. 31,32 Bioclimatic variables reflect different characteristics of annual trends, seasonal patterns, and extreme or limiting environmental factors of temperature and precipitation, and are therefore related to the ecological niche of insect species 9,19 and often used in ecological modeling techniques. Hence, the 19 current bioclimatic variables, which are average for the years 1970-2000, were obtained from WorldClim version 2.1.…”

“…The reproduction, distribution, migration, and adaptation of insects can be directly influenced by climatic factors such as temperature, and precipitation 5,6 . Climate change alters the relative abundance and geographical range of many insect species 7–9 . Consequently, it is inferred that the adaptability and geographical distribution of the insect tribe Zyginellini may also be affected by climate change.…”

“…5,6 Climate change alters the relative abundance and geographical range of many insect species. [7][8][9] Consequently, it is inferred that the adaptability and geographical distribution of the insect tribe Zyginellini may also be affected by climate change.…”